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This chapter is devoted to the most popular heuristic partitional clustering algorithms such as k-means, k-medians, and k-medoids. In addition, we give an overview of some clustering algorithms based on mixture models, self-organizing map, and fuzzy clustering. The description of these algorithms and their flowcharts are presented. Convergence results for the k-means and the k-medians algorithms using nonsmooth optimization techniques are discussed.

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Heuristic Clustering Algorithms

  • 章节

  • 发表日期：

    2025年

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  • Adil Bagirov,
  • Napsu Karmitsa,
  • Sona Taheri

摘要

This chapter is devoted to the most popular heuristic partitional clustering algorithms such as k-means, k-medians, and k-medoids. In addition, we give an overview of some clustering algorithms based on mixture models, self-organizing map, and fuzzy clustering. The description of these algorithms and their flowcharts are presented. Convergence results for the k-means and the k-medians algorithms using nonsmooth optimization techniques are discussed.